Benefits and costs of<i>Leptophlebia</i>(Ephemeroptera) mayfly movements between river channels and floodplain wetlands
Bibliographic record
Abstract
Dramatic drift of nymphs of the mayflies Leptophlebia Westwood, 1840 and Siphlonurus Eaton, 1868 (47 600 individuals/trap per hour) was observed between a southeastern USA river and adjacent floodplain following natural flooding events. Active movements of these nymphs against the water flow were also detected. Large numbers of leptophlebid nymphs reside in floodplains during the winter and spring, but how and why they colonize and develop in temporary habitats is uncertain. We detected few environmental advantages (i.e., temperature, food abundance or quality) for mayflies in floodplains compared with river habitats. Despite this, experiments indicated that mayflies had 36% higher growth rates in the floodplain than in the river and demonstrated tolerance to short-term drying (up to 12 d). Migration entails costs of migrating against flows during daylight when vulnerability to predation is high, colonizing a habitat subject to drying, hypoxia, and supporting amphibian predators, with few apparent benefits. Dispersal into wetlands may be attributed to avoiding swift river flows or exploiting largely fishless habitats. However, dispersal could be an evolutionary relic of behavior beneficial in more northerly habitats; our study populations of Leptophlebia mayflies were at the southern extreme of their range and perhaps operating suboptimally. Our results emphasize the importance of river–floodplain linkages to the ecology of both habitats.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".